Economic Evaluation of Exercise or Cognitive and Social Enrichment Activities for Improved Cognition After Stroke

Key Points Question What is the cost-effectiveness of exercise or cognitive and social enrichment activities to improve cognition among older adults with chronic stroke? Findings In this economic evaluation with 120 older adults from a randomized clinical trial, the multicomponent exercise program conducted over a 6-month period was cost-effective for cognitive function, with limited impact on health-related quality of life. Cognitive and social enrichment activities incurred higher costs compared with the balance and tone control group. Meaning These findings suggest that multicomponent exercise may be a cost-effective approach to improving cognitive function in older adults with chronic stroke.

When missing data is not handled appropriately, this may lead to biased results and findings from cost-effectiveness analysis. 1,3The method to address missing data is informed by the assumption of the missing data mechanism. 4issing data may be classified as missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).MCAR describes a mechanism where neither the missing data is independent of observed nor unobserved factors. 5MAR describes a mechanism where missingness is unrelated to the unobserved values. 5NAR describes a mechanism where the unobserved variable itself predicts missingness. 5While is it difficult to examine if MAR and MNAR hold for a particular dataset, it is possible to investigate if the assumption of MCAR holds. 1 For instance, data is unlikely to be MCAR if missing data differs by treatment group or baseline variables predict missingness. 1 We examined associations between baseline variables and missing data for the outcomes of interests using logic regression presented in Table 1.
MAR data mechanism was assumed and multiple imputation was used to predict estimates for missing costs and effectiveness data. 1,4,6,7Multiple involves replacing missing values with plausible imputed datasets that are combined to account for uncertainty about the missing data.

Figure 1 . 9 Figure 2 .
Figure 1.Consort flow diagram for cost-effectiveness analysis, adapted from the Vitality primary paper.9

Table 1 . Logistic regression for missingness of costs, quality-adjusted life-years on baseline variables
10 used Multiple Imputation by Chained Equation (MICE) in STATA to address missing data by specifying one imputation model for each variable of interest (i.e.costs, ADAS-Cog-Plus, and Quality Adjusted Life Years (QALYs)).Five-thousand iterations of bootstrapping were used to quantify uncertainty and determine which values were more likely.10Pmm(knn)represents"predictivemean matching".This ensured that the imputed values for missing costs and effectiveness outcomes were in an acceptable range.1 c) Missing data variable represents either one of cost, ADAS-Cog-Plus and QALY variables with missing data d) Complete baseline variable represents auxiliary variables that were found to be associated with missingness based on results from the logistic regression presented in Table1.e) Add (number of imputation) represented the number of imputations specified in our model which was 50.f) By treatment group ensured that the values were imputed by different treatment groups.

eTable 1. Number and proportion of participants with complete data in Vitality study
© 2023 Adjetey C et al.JAMA Network Open.eTable 2.

Results of sensitivity analyses Scenario Outcomes Intervention cessation (at 6 months) End of follow-up (at 12 months)
Reference indicates that the comparator is the stretching and toning (control) group.b There is no WTP for which we can be 95% confident that the two therapies differ in value.c QALYs are adjusted for baseline utility using a linear regression model.d Confidence interval is written as [lower limit, upper limit] and interpreted as: for WTP ≥ 0 & ≤ 14589: We can be 95% confident that the therapy with the larger point estimate for effect represents good value compared with the alternative.e Confidence interval is written as [lower limit, upper limit] and interpreted as: there is no WTP for which we can be 95% confident that the 2 therapies differ in value.